The sense of hearing in human beings involves the use of hair cells in the cochlea that convert or transduce acoustic signals into auditory nerve impulses. Hearing loss, which may be due to many different causes, is generally of two types: conductive and sensorineural. Conductive hearing loss occurs when the normal mechanical pathways for sound to reach the hair cells in the cochlea are impeded. These sound pathways may be impeded, for example, by damage to the auditory ossicles. Conductive hearing loss may often be helped by the use of conventional hearing aids that amplify sound so that acoustic signals reach the cochlea and the hair cells. Some types of conductive hearing loss may also be treated by surgical procedures.
Sensorineural hearing loss, on the other hand, is due to the absence or the destruction of the hair cells in the cochlea which are needed to transduce acoustic signals into auditory nerve impulses. Thus, people who suffer from sensorineural hearing loss are unable to derive any benefit from conventional hearing aid systems.
To overcome sensorineural hearing loss, numerous cochlear implant systems—or cochlear prosthesis—have been developed. These devices seek to bypass the hair cells in the cochlea by presenting electrical stimulation directly to the auditory nerve fibers. This leads to the perception of sound in the brain and at least partial restoration of hearing function. To facilitate direct stimulation of the auditory nerve fibers, an array of electrodes may be implanted in the cochlea. A sound processor processes an incoming sound and translates it into electrical stimulation pulses applied by these electrodes which directly stimulate the auditory nerve.
Many cochlear implant systems, as well as other types of neural stimulators, are configured to measure the effectiveness of an electrical stimulation current applied to neural tissue (e.g., the auditory nerve) by using a process known as neural response imaging (NRI). In NRI, the neural stimulator delivers an electrical stimulus to the neural tissue with a stimulating electrode and then records the resulting electrical activity of the neural tissue with a recording electrode. This resulting electrical activity is often referred to as an evoked neural response and occurs when the neural tissue depolarizes in response to the applied stimulus.
An evoked neural response may serve as a diagnostic measure to determine whether the neural stimulator is functioning correctly. NRI may also be used to determine optimal stimulation parameters for each electrode or electrode configuration. For example, NRI may be used to determine the lowest level of stimulation current that is required to evoke a neural response in a particular nerve. This information may then be used to optimize the stimulation parameters or settings of the cochlear implant system. NRI may also be used for a number of additional reasons.
In practice, however, the signal recorded by the recording electrode often includes undesirable signals that interfere with detection of the desired neural response. The terms “neural recording” and “neural recording signal” will be used herein and in the appended claims, unless otherwise specifically denoted, to refer to any signal recorded by the recording electrode. As will be explained in more detail below, a neural recording signal may include any combination of a neural response signal, noise, and/or stimulus artifact. Neural recording signals are sometimes referred to as evoked potential recordings.
As mentioned, a neural recording signal may include noise. Noise refers to any signal that is not correlated with the stimulus that is applied to the neural tissue by the neural stimulator. Noise is generally unpredictable.
Furthermore, a neural recording signal may also include stimulus artifact. Stimulus artifact includes signals, other than the neural response, that are correlated with the stimulus that is used to evoke the neural response. For example, the stimulus artifact may include the voltage potential of the stimulus pulse itself. Another source of stimulus artifact is cross-talk between the recording circuit and the stimulation circuit.
The presence of noise and stimulus artifact often makes it difficult to determine whether a neural recording includes a neural response. A number of conventional techniques exist for removing noise and stimulus artifact from a signal. However, these techniques are often ineffective when applied to a neural recording signal.
For example, filtering may be used to remove noise that has a different frequency than the frequency of a particular signal of interest. However, in neural stimulation systems, the frequency of the noise and the frequency of an evoked neural response signal are often similar. Thus, conventional filtering cannot always be used to remove noise from a neural recording.
Signal correlation may also be used to remove noise from a signal of interest. In signal correlation, a measured signal is correlated with a known reference signal to remove uncorrelated noise from the measured signal. However, evoked neural responses are often variable from patient to patient. Hence, a single reference signal cannot be used to correlate evoked neural responses from multiple patients. The signal correlation technique is therefore ineffective in many instances in removing noise from a neural recording.
Likewise, a number of conventional techniques exist for removing stimulus artifact from a neural recording. These techniques include alternating polarity, forward masking, third-phase compensation, and scaled template techniques. For example, in the alternating polarity technique, the neural response within the neural recording is estimated to be the average of the responses to a first stimulation pulse having a first polarity (e.g. cathodic) and a second stimulation pulse having the opposite polarity (e.g. anodic). The neural response stays the same polarity with the reverse in polarity of the stimulus. However, the stimulus artifact reverses polarity with the reverse in polarity of the stimulus. Consequently, the average response to the two polarities has a lower artifact component than either of the responses taken by themselves. While the alternating polarity technique is sometimes successful in reducing stimulus artifact in a neural recording, it does not eliminate it in all cases. Furthermore, the alternating polarity, as well as the other conventional techniques, often leaves large, residual stimulus artifacts in the neural recording.
As mentioned, it is often desirable to determine the minimum stimulation current level needed to evoke a neural response. This minimum stimulation current level is referred to as a “neural response threshold current level” or simply as a “neural response threshold.” The neural stimulator may then be configured to apply effective, comfortable, and optimal stimulus levels that conserve the power available to the stimulator. However, when a neural recording signal is marred by noise and artifact signals, it is often difficult to visually distinguish between a neural recording signal that includes a neural response signal and a neural recording signal that does not include a neural response signal. Thus, it is often difficult to determine the neural response threshold current level.